These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

161 related articles for article (PubMed ID: 29024534)

  • 1. Rationalizing Promiscuity Cliffs.
    Dimova D; Bajorath J
    ChemMedChem; 2018 Mar; 13(6):490-494. PubMed ID: 29024534
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Exploring structure-promiscuity relationships using dual-site promiscuity cliffs and corresponding single-site analogs.
    Hu H; Bajorath J
    Bioorg Med Chem; 2020 Jan; 28(1):115238. PubMed ID: 31818631
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Systematic computational identification of promiscuity cliff pathways formed by inhibitors of the human kinome.
    Miljković F; Vogt M; Bajorath J
    J Comput Aided Mol Des; 2019 Jun; 33(6):559-572. PubMed ID: 30915709
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Activity profile relationships between structurally similar promiscuous compounds.
    Hu Y; Bajorath J
    Eur J Med Chem; 2013 Nov; 69():393-8. PubMed ID: 24077530
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Matched molecular pair analysis of small molecule microarray data identifies promiscuity cliffs and reveals molecular origins of extreme compound promiscuity.
    Dimova D; Hu Y; Bajorath J
    J Med Chem; 2012 Nov; 55(22):10220-8. PubMed ID: 23050678
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Structure-Promiscuity Relationship Puzzles-Extensively Assayed Analogs with Large Differences in Target Annotations.
    Hu Y; Jasial S; Gilberg E; Bajorath J
    AAPS J; 2017 May; 19(3):856-864. PubMed ID: 28265982
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Analyzing Promiscuity at the Level of Active Compounds and Targets.
    Bajorath J
    Mol Inform; 2016 Dec; 35(11-12):583-587. PubMed ID: 27870240
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of Promiscuity Cliffs Using Machine Learning.
    Blaschke T; Feldmann C; Bajorath J
    Mol Inform; 2021 Jan; 40(1):e2000196. PubMed ID: 32881355
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Design of multitarget activity landscapes that capture hierarchical activity cliff distributions.
    Dimova D; Wawer M; Wassermann AM; Bajorath J
    J Chem Inf Model; 2011 Feb; 51(2):258-66. PubMed ID: 21275393
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Data structures for compound promiscuity analysis: promiscuity cliffs, pathways and promiscuity hubs formed by inhibitors of the human kinome.
    Miljković F; Bajorath J
    Future Sci OA; 2019 Jul; 5(7):FSO404. PubMed ID: 31428450
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Mapping of inhibitors and activity data to the human kinome and exploring promiscuity from a ligand and target perspective.
    Hu Y; Kunimoto R; Bajorath J
    Chem Biol Drug Des; 2017 Jun; 89(6):834-845. PubMed ID: 27933727
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prediction of individual compounds forming activity cliffs using emerging chemical patterns.
    Namasivayam V; Iyer P; Bajorath J
    J Chem Inf Model; 2013 Dec; 53(12):3131-9. PubMed ID: 24304008
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Method for the evaluation of structure-activity relationship information associated with coordinated activity cliffs.
    Dimova D; Stumpfe D; Bajorath J
    J Med Chem; 2014 Aug; 57(15):6553-63. PubMed ID: 25014781
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Systematic Assessment of Molecular Selectivity at the Level of Targets, Bioactive Compounds, and Structural Analogues.
    Hu Y; Bajorath J
    ChemMedChem; 2016 Jun; 11(12):1362-70. PubMed ID: 26358784
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Enhancing Molecular Promiscuity Evaluation Through Assay Profiles.
    Avram S; Curpan R; Bora A; Neanu C; Halip L
    Pharm Res; 2018 Oct; 35(11):240. PubMed ID: 30338400
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Introduction of target cliffs as a concept to identify and describe complex molecular selectivity patterns.
    Hu Y; Bajorath J
    J Chem Inf Model; 2013 Mar; 53(3):545-52. PubMed ID: 23379346
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Data structures for computational compound promiscuity analysis and exemplary applications to inhibitors of the human kinome.
    Miljković F; Bajorath J
    J Comput Aided Mol Des; 2020 Jan; 34(1):1-10. PubMed ID: 31792884
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Extending the activity cliff concept: structural categorization of activity cliffs and systematic identification of different types of cliffs in the ChEMBL database.
    Hu Y; Bajorath J
    J Chem Inf Model; 2012 Jul; 52(7):1806-11. PubMed ID: 22758389
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MMP-Cliffs: systematic identification of activity cliffs on the basis of matched molecular pairs.
    Hu X; Hu Y; Vogt M; Stumpfe D; Bajorath J
    J Chem Inf Model; 2012 May; 52(5):1138-45. PubMed ID: 22489665
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comprehensive analysis of three-dimensional activity cliffs formed by kinase inhibitors with different binding modes and cliff mapping of structural analogues.
    Furtmann N; Hu Y; Bajorath J
    J Med Chem; 2015 Jan; 58(1):252-64. PubMed ID: 25054653
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.